Learning in Neural Circuits

Comparison of distributions of simple cells RFs and RFs developed by different models. Blue dots mark the column model in Lücke, Neural Comp, 2009

In this project computational models of learning in neural microcircuits are studied. The studied systems are motivated by recent data on synaptic plasticity and on on the fine-scale structure of neural circuits. We study the implications of such models for learning and compare the resulting neural response properties to experimental data.

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The papers listed above have been published after peer review in different journals. These journals remain the only definitive repository of the content. Copyright and all rights therein are usually retained by the respective publishers. These materials may not be copied or reposted without their explicit permission. Use for scholarly purposes only.